GCP Data Architect

HCLTech; Lucknow; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

HCLTech is seeking a highly experienced GCP Data Architect to lead the design and implementation of scalable, secure data platforms on Google Cloud. You will architect end-to-end pipelines and data models to support enterprise transformations.

The role requires hands-on expertise with BigQuery, Dataflow, Pub/Sub, and a strong governance posture. You will mentor teams and drive performance, cost efficiency, and reliable operation across platforms.

Qualifications

• 10+ years of experience in Data Engineering / Data Architecture.
• Deep expertise in GCP data services and modern data architectures.
• Strong hands-on capability and enterprise data transformation experience.
• Bachelor’s or Master’s degree in CS/IT or related field.

Responsibilities

• Architect and implement end-to-end data platforms on Google Cloud Platform (GCP).
• Design scalable batch and real-time data pipelines using BigQuery, Dataflow, Pub/Sub.
• Define and optimize data storage & processing architectures using BigQuery, Cloud Storage, Cloud SQL, Firestore.
• Lead development of robust data models, data warehouses, and data lakes.
• Establish data governance, quality, security, and compliance frameworks.
• Collaborate with business stakeholders, data scientists, and engineering teams.
• Drive performance optimization, cost efficiency, and reliability across data platforms.
• Provide technical leadership, conduct design reviews, and mentor engineering teams.
• Define and enforce best practices, standards, and reusable frameworks.
• Evaluate and adopt emerging GCP services and modern data architecture patterns.

Skills

BigQuery

Dataflow

Pub/Sub

Cloud Storage

Cloud SQL

Firestore

Python

SQL

ETL/ELT

Data Warehousing

Data Modeling

Data Governance

Star Schema

Metadata & lineage

Education

Bachelor's in CS/IT

Master's degree

Tools

Apache Beam

Airflow

Cloud Composer

Terraform

Spark

Hadoop

Job description

About the Role

We are looking for a highly experienced GCP Data Architect to lead the design and implementation of scalable, secure, and high-performance data platforms on Google Cloud. This role requires deep expertise in modern data architectures, strong hands-on capability, and the ability to drive enterprise-level data transformation initiatives.

Responsibilities

• Architect and implement end-to-end data platforms on Google Cloud Platform (GCP).
• Design and build scalable batch and real-time data pipelines using:
• Big Query, Dataflow (Apache Beam), Pub/Sub
• Define and optimize data storage & processing architectures using:
• Big Query, Cloud Storage, Cloud SQL, Fire store
• Lead development of robust data models, data warehouses, and data lakes.
• Establish data governance, quality, security, and compliance frameworks.
• Collaborate with business stakeholders, data scientists, and engineering teams to translate requirements into scalable solutions.
• Drive performance optimization, cost efficiency, and reliability across data platforms.
• Provide technical leadership, conduct design reviews, and mentor engineering teams.
• Define and enforce best practices, standards, and reusable frameworks.
• Evaluate and adopt emerging GCP services and modern data architecture patterns.

Qualifications

• Bachelor’s/master’s degree in computer science, IT, or related field
• 10+ years of experience in Data Engineering / Data Architecture

Required Skills

• GCP Services:
• Big Query (Advanced level)
• Dataflow (Apache Beam)
• Pub/Sub
• Cloud Storage
• Cloud SQL / Fire store
• Data Engineering & Architecture: ETL/ELT pipeline design (batch & streaming), Data Warehousing & Data Modeling (Star, Snowflake), Distributed data processing, Real-time data architecture
• Programming: Python, SQL (mandatory)
• Architecture Expertise: End-to-end data platform design, Data governance & security models, Metadata, lineage, and cataloging

Preferred Skills

• GCP Certifications: Professional Data Engineer / Cloud Architect
• Experience with:
• Apache Spark / Hadoop ecosystem
• Machine Learning & AI pipeline integration
• Exposure to: CI/CD, DevOps practices, Terraform, Workflow orchestration (Airflow / Cloud Composer)